Gaza Genocide

Libraries

Data

gaza_geno <- read.csv("D:/R_Gaza/gaza/data/killed-in-gaza.csv")
class(gaza_geno)

## [1] "data.frame"

First data exploration

gaza_geno <- as_tibble(gaza_geno)
class(gaza_geno)

## [1] "tbl_df"     "tbl"        "data.frame"

gaza_geno

## # A tibble: 34,344 × 7
##    id          name                       en_name         age dob   sex   source
##    <chr>       <chr>                      <chr>         <int> <chr> <chr> <chr> 
##  1 طفللللللل   بنت اسيا نزار محمد ابووردة Bint Asaia N…     0 2024… f     h     
##  2 طفللللل     ابن ولاء     الدوواسة      Abn Wlaa Ald…     0 2024… m     h     
##  3 طفل رضيع66  أمل محمد جمعة أبو صويص     Amal Muhamma…     0 2023… f     c     
##  4 طفل رضيع6   ياسر صلاح ياسر الدلو       Yasr Salah Y…     0 2023… m     h     
##  5 طفل رضيع55  كارمل علاء وليد حمدان      Karml Alaaa …     0 2023… f     c     
##  6 طفل رضيع5   ميساء ديب محمود السكافى    Maisaa Diab …     0 2023… f     c     
##  7 طفل رضيع4   محمد نعيم نصر عياد         Muhammad Nai…     0 2023… m     c     
##  8 طفل رضيع3   كنان شادي هاشم مشتهى       Knan Shadi H…     0 2023… m     c     
##  9 طفل رضيع226 ابن/ انوار احمد محمد درويش Abn/ Anwar A…     0 2023… m     h     
## 10 طفل رضيع225 بنت/زينب محمد العبد نواس   Daughter of …     0 2023… f     h     
## # ℹ 34,334 more rows

death_by_age <- 
  gaza_geno %>% 
  group_by(age = as.integer(age)) %>% 
  summarise(Death = n())

peak_10_ages <- death_by_age %>% 
  top_n(n = 10, Death) %>% 
  pull(age)

age_quantiles <- quantile(gaza_geno$age)
age_quantiles <- as.matrix(age_quantiles)
age_quantiles_rownames <- rownames(age_quantiles)
age_quantiles <- as.tibble(cbind(age_quantiles, age_quantiles_rownames))

## Warning: `as.tibble()` was deprecated in tibble 2.0.0.
## ℹ Please use `as_tibble()` instead.
## ℹ The signature and semantics have changed, see `?as_tibble`.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

## Warning: The `x` argument of `as_tibble.matrix()` must have unique column names if
## `.name_repair` is omitted as of tibble 2.0.0.
## ℹ Using compatibility `.name_repair`.
## ℹ The deprecated feature was likely used in the tibble package.
##   Please report the issue at <https://github.com/tidyverse/tibble/issues>.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.

colnames(age_quantiles)

## [1] "V1"                     "age_quantiles_rownames"

colnames(age_quantiles)<- c("Age", "Quantile")

age_quantiles %>% kbl(caption = "Age quantiles of murdered palestinians") %>% kable_classic() %>% kable_styling(full_width = FALSE, )

Age quantiles of murdered palestinians

Age	Quantile
0	0%
14	25%
26	50%
39	75%
101	100%

peak_10_ages

##  [1]  0 16 17 23 28 29 30 31 32 33

death_by_sex_age <- 
  gaza_geno %>% 
  mutate(sex = factor(sex, levels = c("f", "m"), 
                      labels = c("Female", "Male"))) %>% 
  group_by(age, sex, .groups = TRUE) %>% 
  summarise(Death = n())

## `summarise()` has grouped output by 'age', 'sex'. You can override using the
## `.groups` argument.

death_by_sex_age <- death_by_sex_age[-3]

tbl_by_sex_age <- gaza_geno %>% 
  select(sex, age) %>% 
  mutate(sex = factor(sex, levels = c("f", "m"), labels = c("Female", "Male"))) %>% 
  tbl_summary(label = list(sex = "Sex", age = "Age")) 

tbl_by_sex_age

Characteristic	N = 34,3441
Sex
Female	12,370 (36%)
Male	21,974 (64%)
Age	26 (14, 39)
1 n (%); Median (Q1, Q3)

Plots

theme_set(theme_bw())

gaza_geno %>% 
  ggplot(aes(x = age))+
  geom_histogram(fill = "#4D5052", colour = "black", bins = 20, binwidth = 2)+
  scale_x_continuous(breaks = seq(0, 100, 20))+
  labs(title = "Gaza genocide - Death by Age", x = "Age", y = "Frequency of Deaths", 
       caption = "The frequency of murdered palestinians by age (murdered by the Israelis)")+
  theme(plot.title = element_text(face = "bold"), 
        plot.caption = element_text(face = "italic", colour = "#4D5052"), 
        plot.caption.position = "plot")

ggsave(filename = "geno_hist.pdf", path = "D:/R_Gaza/pal_map/images")

## Saving 7 x 5 in image

death_by_age %>% 
  ggplot(aes(x = age, y = Death))+
  geom_line()+
  geom_segment(x = 14, xend= 14, y = 0, yend = 659, linetype = "dashed")+
  geom_segment(x = 26, xend= 26, y = 0, yend = 652, linetype = "dashed")+
  geom_segment(x = 39, xend= 39, y = 0, yend = 469, linetype = "dashed")+
  scale_x_continuous(breaks = seq(0, 100, 20))+
  labs(title = "Gaza genocide - Death by Age", x = "Age", y = "Number of Deaths", 
       caption = "The number of murdered palestinians by age (murdered by the Israelis)")+
  theme(plot.title = element_text(face = "bold"), 
        plot.caption = element_text(face = "italic", colour = "#4D5052"), 
        plot.caption.position = "plot")

ggsave(filename = "geno_linechart.pdf", path = "D:/R_Gaza/pal_map/images")

## Saving 7 x 5 in image

Maps

Setting the data

# Get palestinian cities, convert it to sf dataframe, assign projection to the coordinates and save it

data(world.cities)
palestine_cities <- world.cities %>% filter(country.etc == "Palestine")
class(palestine_cities)

## [1] "data.frame"

palestine_cities <- as_tibble(palestine_cities)
write_excel_csv(palestine_cities, file = "D:/R_Gaza/pal_map/data/palestinians_cities.csv")

names(palestine_cities)    #get the names for the coordinate variables

## [1] "name"        "country.etc" "pop"         "lat"         "long"       
## [6] "capital"

palestine_cities_sf <- st_as_sf(palestine_cities, coords = c("lat", "long")) #convert to sf df tibble
class(palestine_cities_sf) #check if class has changed to sf dataframe tibble

## [1] "sf"         "tbl_df"     "tbl"        "data.frame"

st_crs(palestine_cities_sf) #check for geographic projections

## Coordinate Reference System: NA

st_crs(palestine_cities_sf) <- 4326  #assign geographic projection (4326, i.e., longlat WGS84)
st_crs(palestine_cities_sf) #check if the geographic projection was assigned

## Coordinate Reference System:
##   User input: EPSG:4326 
##   wkt:
## GEOGCRS["WGS 84",
##     ENSEMBLE["World Geodetic System 1984 ensemble",
##         MEMBER["World Geodetic System 1984 (Transit)"],
##         MEMBER["World Geodetic System 1984 (G730)"],
##         MEMBER["World Geodetic System 1984 (G873)"],
##         MEMBER["World Geodetic System 1984 (G1150)"],
##         MEMBER["World Geodetic System 1984 (G1674)"],
##         MEMBER["World Geodetic System 1984 (G1762)"],
##         MEMBER["World Geodetic System 1984 (G2139)"],
##         ELLIPSOID["WGS 84",6378137,298.257223563,
##             LENGTHUNIT["metre",1]],
##         ENSEMBLEACCURACY[2.0]],
##     PRIMEM["Greenwich",0,
##         ANGLEUNIT["degree",0.0174532925199433]],
##     CS[ellipsoidal,2],
##         AXIS["geodetic latitude (Lat)",north,
##             ORDER[1],
##             ANGLEUNIT["degree",0.0174532925199433]],
##         AXIS["geodetic longitude (Lon)",east,
##             ORDER[2],
##             ANGLEUNIT["degree",0.0174532925199433]],
##     USAGE[
##         SCOPE["Horizontal component of 3D system."],
##         AREA["World."],
##         BBOX[-90,-180,90,180]],
##     ID["EPSG",4326]]

st_crs(palestine_cities_sf)$proj4string

## [1] "+proj=longlat +datum=WGS84 +no_defs"

palestine_cities_sf #check if "lat" and "long" variables were changed to "geometry" variable.

## Simple feature collection with 244 features and 4 fields
## Geometry type: POINT
## Dimension:     XY
## Bounding box:  xmin: 31.27 ymin: 34.25 xmax: 32.55 ymax: 35.45
## Geodetic CRS:  WGS 84
## # A tibble: 244 × 5
##    name               country.etc   pop capital      geometry
##  * <chr>              <chr>       <int>   <int>   <POINT [°]>
##  1 'Abasan al-Jadidah Palestine    5629       0 (31.31 34.34)
##  2 'Abasan al-Kabirah Palestine   18999       0 (31.32 34.35)
##  3 'Abud              Palestine    2456       0 (32.03 35.07)
##  4 'Abwein            Palestine    3434       0  (32.03 35.2)
##  5 'Ajjah             Palestine    5143       0  (32.37 35.2)
##  6 'Anabta            Palestine    7311       0 (32.31 35.12)
##  7 'Anata             Palestine    9149       0 (31.81 35.28)
##  8 'Anin              Palestine    3717       0  (32.5 35.17)
##  9 'Anzah             Palestine    2006       0 (32.37 35.22)
## 10 'Aqbah Jabbar      Palestine    6337       0 (31.83 35.45)
## # ℹ 234 more rows

st_write(palestine_cities_sf, "D:/R_Gaza/pal_map/data/palestinian_cities", 
         driver = "ESRI Shapefile", delete_layer = TRUE)  # save the sf data frame as shapefile

## Deleting layer `palestinian_cities' using driver `ESRI Shapefile'
## Writing layer `palestinian_cities' to data source 
##   `D:/R_Gaza/pal_map/data/palestinian_cities' using driver `ESRI Shapefile'
## Writing 244 features with 4 fields and geometry type Point.

unzip(zipfile =  "D:/R_Gaza/gaza/data/localities_palestine_sf.zip" , exdir ="data/localities_palestine")
localities_palestine_sf <- st_read("data/localities_palestine")

## Multiple layers are present in data source D:\R_Gaza\pal_map\data\localities_palestine, reading layer `%D8%AA%D8%AC%D9%85%D8%B9%D8%A7%D8%AA_%D9%81%D9%84%D8%B3%D8%B7%D9%8A%D9%86___Localities_Palestine'.
## Use `st_layers' to list all layer names and their type in a data source.
## Set the `layer' argument in `st_read' to read a particular layer.

## Reading layer `%D8%AA%D8%AC%D9%85%D8%B9%D8%A7%D8%AA_%D9%81%D9%84%D8%B3%D8%B7%D9%8A%D9%86___Localities_Palestine' from data source `D:\R_Gaza\pal_map\data\localities_palestine' using driver `ESRI Shapefile'
## Simple feature collection with 619 features and 10 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 3809204 ymin: 3661924 xmax: 3960023 ymax: 3836009
## Projected CRS: WGS 84 / Pseudo-Mercator

localities_palestine_sf

## Simple feature collection with 619 features and 10 fields
## Geometry type: MULTIPOLYGON
## Dimension:     XY
## Bounding box:  xmin: 3809204 ymin: 3661924 xmax: 3960023 ymax: 3836009
## Projected CRS: WGS 84 / Pseudo-Mercator
## First 10 features:
##    OBJECTID REGIONCODE DISTCODE GOVCODE  LOCCODE                    NAMEAR
## 1         1          2       24    2470 24703430             عبسان الجديدة
## 2         2          2       24    2470 24703470                     خزاعة
## 3         3          2       24    2465 24653200            مخيم دير البلح
## 4         4          2       24    2465 24653275               وادي السلقا
## 5         5          2       24    2455 24552681 أم النصر (القرية البدوية)
## 6         6          2       24    2465 24653065             مخيم النصيرات
## 7         7          2       24    2470 24703420                   خانيونس
## 8         8          2       24    2470 24703425                 بني سهيلا
## 9         9          2       24    2470 24703445             عبسان الكبيرة
## 10       10          2       24    2470 24703485                   الفخاري
##                                  NAMEEN
## 1                     'Abasan al Jadida
## 2                               Khuza'a
## 3                    Deir al Balah Camp
## 4                         Wadi as Salqa
## 5  Um Al-Nnaser (Al Qaraya al Badawiya)
## 6                      An Nuseirat Camp
## 7                            Khan Yunis
## 8                          Bani Suheila
## 9                     'Abasan al Kabira
## 10                         Al Fukhkhari
##                                                                                     NOTES
## 1                                                                                    <NA>
## 2                                                                                    <NA>
## 3                                                                                    <NA>
## 4                                                                                    <NA>
## 5                                                                                    <NA>
## 6                                                                                    <NA>
## 7  تشمل المَواصِي (خانيونس)، وقِيزَان النَجَّار، وقَاعْ الخَرَابَة، وقَاعْ القُرِين، وأُمُّ كَمِيل، وأُّمُّ الكِلاب
## 8                                                                                    <NA>
## 9                                                                                    <NA>
## 10                                                                                   <NA>
##    Shape__Are Shape__Len                       geometry
## 1   4919436.7  11010.191 MULTIPOLYGON (((3824072 367...
## 2   9193057.5  14360.481 MULTIPOLYGON (((3826180 367...
## 3    337604.1   3122.714 MULTIPOLYGON (((3823061 368...
## 4   8752155.1  12611.773 MULTIPOLYGON (((3827289 368...
## 5   4306257.9   9547.706 MULTIPOLYGON (((3844490 370...
## 6   1099596.7  10312.221 MULTIPOLYGON (((3827522 369...
## 7  72893548.1  53756.789 MULTIPOLYGON (((3821981 367...
## 8   9181044.3  16897.216 MULTIPOLYGON (((3823716 367...
## 9  17770337.9  20809.409 MULTIPOLYGON (((3823887 367...
## 10 12900017.9  17496.895 MULTIPOLYGON (((3820790 367...

class(localities_palestine_sf)

## [1] "sf"         "data.frame"

st_crs(localities_palestine_sf)$proj4string

## [1] "+proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs"

localities_palestine_WGS84 <- st_transform(localities_palestine_sf, crs = 4326)
st_crs(localities_palestine_WGS84)$proj4string

## [1] "+proj=longlat +datum=WGS84 +no_defs"

st_write(localities_palestine_WGS84, "D:/R_Gaza/pal_map/data/localities_palestine", 
         driver = "ESRI Shapefile", delete_layer = TRUE)

## Deleting layer `localities_palestine' using driver `ESRI Shapefile'
## Writing layer `localities_palestine' to data source 
##   `D:/R_Gaza/pal_map/data/localities_palestine' using driver `ESRI Shapefile'
## Writing 619 features with 10 fields and geometry type Multi Polygon.

st_crs(localities_palestine_WGS84)$proj4string

## [1] "+proj=longlat +datum=WGS84 +no_defs"

st_crs(palestine_cities_sf)$proj4string

## [1] "+proj=longlat +datum=WGS84 +no_defs"

Creating maps

ggplot(localities_palestine_WGS84)+
  geom_sf(colour = "black")

col_fun <- colorFactor(c("#337bd7", "#c8143b"), domain = NULL)
itamar <- st_point(c(34.82375, 31.89530))
itamarpopup <- c("Where I.J.R was born")   
pal_popup <- paste0("<strong>City Name:</strong>", palestine_cities$name)


palestine_map <- leaflet(localities_palestine_WGS84) %>% 
  addPolygons(stroke = TRUE, weight = 0.7, color = "black", 
              fillColor = ~col_fun(REGIONCODE), 
              group = "Regions", fillOpacity = 0.8) %>% 
  addCircleMarkers(lng = 34.82375 , lat = 31.89530, group = "My House",
                   popup = itamarpopup) %>% 
  addCircleMarkers(data = palestine_cities, group = "Cities", popup = pal_popup, 
                   radius = 0.01, color = "#2c120c") %>% 
  addTiles(group = "OSM") %>% 
  addProviderTiles(provider = "Stadia.OSMBright", group = "OSMBright") %>% 
  addProviderTiles(provider = "Stadia", group = "Stadia") %>%
  addProviderTiles(provider = "Stadia.Outdoors", group = "Outdoors") %>% 
  addProviderTiles(provider = "Stadia.StamenTonerLite", group = "TonerLite") %>% 
  addProviderTiles(provider = "CartoDB", group = "CartoDB") %>% 
  addProviderTiles(provider = "CartoDB.Voyager", group = "CartoDB.Voyager") %>% 
  addProviderTiles(provider = "Esri", group = "Esri") %>% 
  addLayersControl(baseGroups = c("OSM", "OSMBright", "Stadia", "Outdoors", "TonerLite", 
                                  "CartoDB", "CartoDB.Voyager", "Esri"), 
                   overlayGroups = c("Regions", "Where I Live", "Cities"))

## Assuming "long" and "lat" are longitude and latitude, respectively

palestine_map